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Comparison of Intfloat: E5-Large-v2, Krea 3 Edit, VoyageAI by MongoDB: voyage-code-4
3 modelsintfloatIntfloat: E5-Large-v2Remove ×kreaKrea 3 EditRemove ×voyageaiVoyageAI by MongoDB: voyage-code-4Remove ×
What’s differentThe e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy semantic embeddings optimized for retrieval, semantic…Edits and combines reference images using text instructions, with optional prompt expansion, output-size controls, and reproducible generation through a seed.voyage-code-4 is a code embedding model from Voyage AI, a MongoDB company. It is designed for coding agents and code retrieval, with Matryoshka embeddings at 2048, 1024, 512, and 256...
DateNov 22, 2023ListedOct 14, 2026ListedAug 13, 2026Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.025/ megapixelfal · all routes ↗Output + reference images$0.12 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →1 endpoint →1 endpoint →
Context window512—32K
Max output460—28.8K
Parameters———
Open weightsSupportedNot reportedNot reported

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